# Searching Heterogeneous Personal Digital Traces

## TL;DR

This paper introduces a flexible data model based on six questions to organize and search heterogeneous personal digital traces, significantly improving search accuracy across various data sources.

## Contribution

The paper presents a novel, universal data model and search techniques for personal digital traces, enhancing organization and retrieval across diverse data types.

## Key findings

- Improved search accuracy over traditional tools
- Effective aggregation of heterogeneous data sources
- Model applicable to various personal data platforms

## Abstract

Digital traces of our lives are now constantly produced by various connected devices, internet services and interactions. Our actions result in a multitude of heterogeneous data objects, or traces, kept in various locations in the cloud or on local devices. Users have very few tools to organize, understand, and search the digital traces they produce. We propose a simple but flexible data model to aggregate, organize, and find personal information within a collection of a user's personal digital traces. Our model uses as basic dimensions the six questions: what, when, where, who, why, and how. These natural questions model universal aspects of a personal data collection and serve as unifying features of each personal data object, regardless of its source. We propose indexing and search techniques to aid users in searching for their past information in their unified personal digital data sets using our model. Experiments performed over real user data from a variety of data sources such as Facebook, Dropbox, and Gmail show that our approach significantly improves search accuracy when compared with traditional search tools.